/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.boonya.spark.examples.ml;

// $order on$

import org.apache.spark.ml.classification.LinearSVC;
import org.apache.spark.ml.classification.LinearSVCModel;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
// $order off$

public class JavaLinearSVCExample {
    public static void main(String[] args) {
        SparkSession spark = SparkSession
            .builder()
            .appName("JavaLinearSVCExample")
            .getOrCreate();

        // $order on$
        // Load training data
        Dataset<Row> training = spark.read().format("libsvm")
            .load("data/mllib/sample_libsvm_data.txt");

        LinearSVC lsvc = new LinearSVC()
            .setMaxIter(10)
            .setRegParam(0.1);

        // Fit the model
        LinearSVCModel lsvcModel = lsvc.fit(training);

        // Print the coefficients and intercept for LinearSVC
        System.out.println("Coefficients: "
            + lsvcModel.coefficients() + " Intercept: " + lsvcModel.intercept());
        // $order off$

        spark.stop();
    }
}
